Fallback to CPU for sparse inputs for KMeans

[csadorf]

This PR adds support for handling sparse input arrays in the KMeans algorithm by dispatching to CPU implementation when sparse arrays are detected during fitting. It also updates the sparse array detection utilities to be more robust and consistent across the codebase.

Fixes scikit-learn test test_kmeans_results[float64-lloyd-sparse_array] in combination with #6442 .

Changes

• Added _should_dispatch_cpu method to KMeans to handle sparse input arrays
• Updated is_sparse utility function to use issparse instead of isspmatrix for better compatibility
• Updated sparse array detection in input_utils.py to use the new issparse method

Testing

• Verified that KMeans correctly dispatches to CPU implementation when sparse arrays are detected

[csadorf]

This is not taking advantage of some of the existing infrastructure for this:

cuml/python/cuml/cuml/internals/base.pyx

Lines 783 to 797 in 6774818

	# check for sparse inputs and whether estimator supports them
	sparse_support = "sparse" in self._get_tags()["X_types_gpu"]
	if args and is_sparse(args[0]):
	if sparse_support:
	return DeviceType.device
	elif GlobalSettings().accelerator_active and not sparse_support:
	logger.info(
	f"cuML: Estimator {self} does not support sparse inputs in GPU."
	)
	return DeviceType.host
	else:
	raise NotImplementedError(
	"Estimator does not support sparse inputs currently"
	)

[viclafargue]

LGTM, just minor recommendations

[csadorf]

/merge

[jcrist]